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Diffstat (limited to 'textproc/p5-WordNet-Similarity/pkg-descr')
| -rw-r--r-- | textproc/p5-WordNet-Similarity/pkg-descr | 40 |
1 files changed, 18 insertions, 22 deletions
diff --git a/textproc/p5-WordNet-Similarity/pkg-descr b/textproc/p5-WordNet-Similarity/pkg-descr index f58ec498b7c7..aa4c688195df 100644 --- a/textproc/p5-WordNet-Similarity/pkg-descr +++ b/textproc/p5-WordNet-Similarity/pkg-descr @@ -1,27 +1,23 @@ -From the README: - -This package consists of Perl modules along with supporting Perl programs that -implement the semantic relatedness measures described by Leacock Chodorow -(1998), Jiang Conrath (1997), Resnik (1995), Lin (1998), Hirst St Onge (1998) -and the adapted gloss overlap measure by Banerjee and Pedersen (2002). The Perl -modules are designed as object classes with methods that take as input two word -senses. The semantic relatedness of these word senses is returned by these -methods. A quantitative measure of the degree to which two word senses are -related has wide ranging applications in numerous areas, such as word sense -disambiguation, information retrieval, etc. For example, in order to determine -which sense of a given word is being used in a particular context, the sense -having the highest relatedness with its context word senses is most likely to -be the sense being used. Similarly, in information retrieval, retrieving -documents containing highly related concepts are more likely to have higher -precision and recall values. +This package consists of Perl modules along with supporting Perl programs +that implement the semantic relatedness measures described by Leacock +Chodorow (1998), Jiang Conrath (1997), Resnik (1995), Lin (1998), Hirst St +Onge (1998), Wu Palmer (1994), the adapted gloss overlap measure by +Banerjee and Pedersen (2002), and a measure based on context vectors +by Patwardhan (2003). The details of the Vector measure are described in the +Master's thesis work done by Patwardhan (2003) at the University of Minnesota +Duluth. The Perl modules are designed as objects with methods that take as +input two word senses. The semantic relatedness of these word senses is +returned by these methods. A quantitative measure of the degree to which two +word senses are related has wide ranging applications in numerous areas, such +as word sense disambiguation, information retrieval, etc. For example, in +order to determine which sense of a given word is being used in a particular +context, the sense having the highest relatedness with its context word +senses is most likely to be the sense being used. Similarly, in information +retrieval, retrieving documents containing highly related concepts are more +likely to have higher precision and recall values. A command line interface to these modules is also present in the package. The simple, user-friendly interface returns the relatedness measure of two given -words. A number of switches and options have been provided to modify the output -and enhance it with trace information and other useful output. Details of the -usage are provided in other sections of this README. Supporting utilities for -generating information content files from various corpora are also available in -the package. The information content files are required by three of the -measures for computing the relatedness of concepts. +words. WWW: http://search.cpan.org/dist/WordNet-Similarity/ |